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The purpose of this paper is to investigate the microstructures, slag inclusions, morphology and composition of ancient Chinese iron coins exhumed from Emei Mountain and Baoji after 818‐966 years of being imbedded underground.

Metallography, scanning electron microscopy, energy dispersive spectrometry, X‐ray photoelectron spectrometry and Fourier transform infrared spectroscopy were employed.

The results showed that archaeological coins exhibited characteristics of a typical hypoeutectic white cast iron, with slag inclusions of FeS strips and phosphate. Porous or hexagonal platey corrosion products were discovered on the archaeological iron coin, which were mainly identified as Fe₂O₃, FeOOH, Fe_x(OH)_1−xCO₃ and Fe_x(OH)_1−xSO₄. The possible corrosion mechanisms for the iron coins were discussed based on the corrosion products.

This study revealed the characterization of corrosion products on archaeological iron coins and may provide guidance for the preservation of archaeological iron.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

The purpose of this paper is to investigate the proper matches between institutional business ties (to state-owned enterprises (SOEs) and to banks) and firm capabilities (technological capability and marketing capability) in impacting the radical innovation of manufacturing firms in China.

Using the samples of 208 manufacturing firms in China, this study runs three regression models to test all hypotheses.

Ties to SOEs and ties to banks are positively related to radical innovation of manufacturing firms in China. Further, the technological capability and marketing capability have different functions on moderating the relationship between institutional business ties and radical innovation.

The results imply that managers of manufacturing firms should strive to establish close connections to those organizations that are set-up by government in China. In addition, managers should cautious about the synergies between different institutional business ties and different internal capabilities, and properly matching them to develop radical innovation.

This study enriches and extends the managerial ties literature by going beyond previous narrow focus on either business ties or political ties to address a particular type of organization that is set-up by the governments but operate in the business world. The findings of proper ties-capabilities matches provide nuanced understandings to dynamically manage external resources and internal capabilities for the synergetic benefits (e.g. radical innovation). This study also offer a theoretical paradigm (i.e. resource management model) for manufacturing firms to lessen the striking tension between the urgent needs for radical innovation and the hostile ground for conducting radical innovation.

Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues.

This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen.

The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value.

This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues.

As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed.

A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties.

This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.

This paper focuses on governance in higher education in China. It sees that governance as distinctive on the world scale and the potential source of distinctiveness in other domains of higher education. By taking an historical approach, reviewing relevant literature and drawing on empirical research on governance at one leading research university, the paper discusses system organisation, government–university relations and the role of the Communist Party (CCP), centralisation and devolution, institutional leadership, interior governance, academic freedom and responsibility, and the relevance of collegial norms. It concludes that the party-state and Chinese higher education will need to find a Way in governance that leads into a fuller space for plural knowledges, ideas and approaches. This would advance both indigenous and global knowledge, so helping global society to also find its Way.

The purpose of this study is to investigate whether Chinese college students' social cyberloafing out of class has a curvilinear effect on academic performance and whether students' levels of psychological detachment and relaxation mediate the effect.

A field survey was used to collect 502 self-reported responses from student Internet users at a large university located in central China.

The results show an inverted U-shaped relationship between social cyberloafing out of class and academic performance. Two types of effort recovery experience gained from social cyberloafing, psychological detachment and relaxation, mediate that effect. Students' social cyberloafing out of class is positively associated with psychological detachment and relaxation, which in turn, have opposite effects on academic performance.

This study offers novel insights into the effects of social cyberloafing on college students' academic achievement. The findings illustrate how social cyberloafing can serve as a recovery experience and improve academic performance, but it can hinder performance if the cyberloafing is excessive.

This study extends the cyberloafing literature by focusing on Chinese college students' cyberloafing out of class. The study finds that a moderate amount of social cyberloafing out of class can result in psychological detachment, relaxation and improved performance when returning to academic work. However, both too much or too little social cyberloafing can result in difficulty returning to academic work and reduced academic performance. The findings are novel to the cyberloafing literature.